R has a very powerful array slicing ability that allows for some very slick data processing.
Suppose we have a
d“, and for every row where
d$n_observations < 5 we wish to “
NA-out” some other columns (mark them as not yet reliably available). Using slicing techniques this can be done quite quickly as follows.
library("wrapr") d[d$n_observations < 5, qc(mean_cost, mean_revenue, mean_duration)] <- NA
qc()” please see R Tip: Use qc() For Fast Legible Quoting.)
Data Scientist and trainer at Win Vector LLC. One of the authors of Practical Data Science with R.